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In computer vision, the motion field is an ideal representation of motion in three-dimensional space (3D) as it is projected onto a camera image. Given a simplified camera model, each point (,) in the image is the projection of some point in the 3D scene but the position of the projection of a fixed point in space can vary with time.
Common problems in this field relate to Estimating the motion field in an image sequence. Estimating the 3D motion of points in the scene based on measurements on image data. Estimation of Ego-motion, the 3D motion of the camera relative to the scene.
Motion control is a sub-field of automation, encompassing the systems or sub-systems involved in moving parts of machines in a controlled manner. Motion control systems are extensively used in a variety of fields for automation purposes, including precision engineering , micromanufacturing , biotechnology , and nanotechnology . [ 1 ]
Image acquisition – A digital image is produced by one or several image sensors, which, besides various types of light-sensitive cameras, include range sensors, tomography devices, radar, ultra-sonic cameras, etc. Depending on the type of sensor, the resulting image data is an ordinary 2D image, a 3D volume, or an image sequence.
Motion analysis is used in computer vision, image processing, high-speed photography and machine vision that studies methods and applications in which two or more consecutive images from an image sequences, e.g., produced by a video camera or high-speed camera, are processed to produce information based on the apparent motion in the images.
Affine motion estimation is a technique used in computer vision and image processing to estimate the motion between two images or frames. It assumes that the motion can be modeled as an affine transformation (translation + rotation + zooming), which is a linear transformation followed by a translation.
Gradient vector flow (GVF), a computer vision framework introduced by Chenyang Xu and Jerry L. Prince, [1] [2] is the vector field that is produced by a process that smooths and diffuses an input vector field. It is usually used to create a vector field from images that points to object edges from a distance.
A Block Matching Algorithm is a way of locating matching macroblocks in a sequence of digital video frames for the purposes of motion estimation.The underlying supposition behind motion estimation is that the patterns corresponding to objects and background in a frame of video sequence move within the frame to form corresponding objects on the subsequent frame.